In this presentation we'll examine a few of the basic features of the Plotly package using the mtcars data set that's prepackaged with R. For additional information on the package you'll want to visit
11/3/2018
In this presentation we'll examine a few of the basic features of the Plotly package using the mtcars data set that's prepackaged with R. For additional information on the package you'll want to visit
To download and install the Plotly package call the install.packages("plotly") function if you haven't already done so.
Using the code below we'll create some box plots to show the displacement amounts for each car by cylinder type (4,6,8). Note that we'll have to convert the cyl variable to a factor variable
library(plotly) mtcars$cyl<-as.factor(mtcars$cyl) p<-plot_ly(mtcars,y=~disp,color = ~cyl,type="box") p
Here we see that if we hover over the plots we can view the quartile amounts of the displacement variable for each cylinder type
The code below computes the mean of the mpg variable for each of the factors for the am variable where "0" represents manual transmission cars and "1" to denote cars with automatic transmissions
mtcars$am<-as.factor(mtcars$am)
averages<-aggregate(mtcars$mpg,by=list(mtcars$am),mean)
averages$Group.1<-as.factor(averages$Group.1)
second_plot<-plot_ly(x=averages$Group.1,y=averages$x,
color=averages$Group.1,type="bar")
second_plot
If we hover the cursor over the bar representing automatic transmissions we can see that those cars have roughly an avg. mpg = 24